Efficient predictive model of zero quantized DCT coefficients for fast video encoding

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

21 Scopus Citations
View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)922-933
Journal / PublicationImage and Vision Computing
Volume25
Issue number6
Publication statusPublished - 1 Jun 2007

Abstract

Discrete cosine transform (DCT), quantization (Q), inverse quantization (IQ) and inverse DCT (IDCT) are the building blocks in video coding standards adopted by ITU-T and MEPG. Under these standards, a lot of computations are required to perform the DCT, Q, IQ and IDCT operations. With this concern, a novel statistical model based on Gaussian distribution is proposed to predict zero quantized DCT (ZQDCT) coefficients in order to reduce the computational complexity of video encoding. Compared with other predictive models in the literature, the proposed model can detect more ZQDCT coefficients. Simulation results demonstrate that the proposed statistical model is superior to others in terms of speeding up video encoders. Moreover, a hybrid model is derived based on the proposed statistical model and mathematical analysis of individual DCT coefficients to further improve the encoding efficiency. © 2006 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Discrete cosine transform (DCT), Quantization (Q), Video encoding, Zero quantized DCT (ZQDCT) coefficients